Positive and Negative Photolithographic Deposition of Titanium Dioxide from Photosensitive Titanium Complexes
Bibliographic record
Abstract
Lithographic deposition of titanium oxide films using photochemical metal organic deposition from titanium (IV) complexes is demonstrated in this paper. In this paper we explore the chemistry of thin films of titanium (IV) di-n-butoxide bis(2-ethylhexanoate), titanium (IV) di-n-butoxide bis(2-ethyl-2-hydroxybutyrate), titanium (IV) diisopropoxide bis(2,4-pentanedionate), and titanium (IV) diisopropoxide bis(ethyl acetoacetate). These complexes could all be prepared by ligand exchange reaction from the appropriate precursors. Thin films of each of these compounds could be cast by spin coating from solutions. All the complexes underwent photodecomposition to form titanium dioxide films although only titanium (IV) di-n-butoxide bis(2-ethylhexanoate) did so without the formation of an intermediate. Since all of the precursors were soluble negative lithography resulted in the direct deposition of titanium dioxide from these precursors. In contrast we were only able to demonstrate positive lithography on all the films except those constructed from titanium (IV) di-n-butoxide bis(2-ethylhexanoate). Positive lithography was conducted by exposing a region developing to remove film in the exposed regions followed by blanket exposure to convert the remaining regions to titanium dioxide. Patterns of titanium oxide with a feature size of 1 micron and a resolution of 1 micron were routinely achieved by both positive and negative photolithography. These precursors are also potential candidates for deep UV lithography in fabricating features of sub-50 nanometres.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".